Enhancing forecasting capabilities in pharma

A global top-20 pharmaceutical company had inconsistent forecasting expertise across regional teams. Evaluate designed a customized, interactive virtual training program to standardize forecasting practices, combining progressive learning, real-world case studies, quizzes, breakout sessions, and structured Q&As. This produced "improved forecasting accuracy, confidence, and a consistent knowledge baseline across teams," and the client later expanded the program with advanced modules. One trainee said: "Excellent content. It was very helpful and I would recommend it to my team members."

The customer is anonymised in Norstella’s own case study — not withheld by us.

Norstella is a holding company merging several pharma-intelligence brands — Citeline (trial intelligence), Evaluate (forecasting), MMIT (payer/formulary data) and Panalgo (real-world analytics) — into one data asset.

This sits in the Data Providers stage of the AI use-case lifecycle: Named examples from the real-world-data, claims and competitive-intelligence providers pharma AI systems are trained on, benchmarked against, or run inside of.